from sklearn_benchmarks.reporting.hp_match import HpMatchReporting
reporting = HpMatchReporting(against_lib="onnx", config="config.yml", log_scale=True)
reporting.make_report()
We assume here there is a perfect match between the hyperparameters of both librairies. For a given set of parameters and a given dataset, we compute the speedup
time scikit-learn / time onnx. For instance, a speedup of 2 means that onnx is twice as fast as scikit-learn for a given set of parameters and a given dataset.
KNeighborsClassifier_brute_force¶onnx (1.10.1) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=brute.
| estimator | function | n_samples_train | n_samples | n_features | parameters_digest | dataset_digest | mean_duration_sklearn | std_duration_sklearn | n_iter | ... | algorithm | n_jobs | n_neighbors | accuracy_score_sklearn | mean_duration_onnx | std_duration_onnx | accuracy_score_onnx | speedup | std_speedup | diff_accuracy_scores | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | e70d8e7886766d41f30889506baa1e67 | 2cf49829391aa7891e877f2ed070adf0 | 2.027753 | 0.260970 | NaN | ... | brute | -1 | 1 | 0.663 | 0.333881 | 0.012534 | 1.000 | 6.073273 | 6.077551 | 0.337 |
| 2 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | e70d8e7886766d41f30889506baa1e67 | 2cf49829391aa7891e877f2ed070adf0 | 0.025990 | 0.002125 | NaN | ... | brute | -1 | 1 | 1.000 | 17.823298 | 0.265818 | 0.757 | 0.001458 | 0.001458 | 0.243 |
| 4 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 22d5eac4a4146149b35eae6914921514 | 2cf49829391aa7891e877f2ed070adf0 | 2.776739 | 0.044499 | NaN | ... | brute | -1 | 5 | 0.757 | 17.679337 | 0.066352 | 0.882 | 0.157061 | 0.157062 | 0.125 |
| 7 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 16f94fc93942ff7ece860c9b0f64645f | 2cf49829391aa7891e877f2ed070adf0 | 2.158312 | 0.024728 | NaN | ... | brute | 1 | 100 | 0.882 | 0.334007 | 0.006963 | 1.000 | 6.461870 | 6.463274 | 0.118 |
| 8 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 16f94fc93942ff7ece860c9b0f64645f | 2cf49829391aa7891e877f2ed070adf0 | 0.023255 | 0.000925 | NaN | ... | brute | 1 | 100 | 1.000 | 17.727084 | 0.051484 | 0.757 | 0.001312 | 0.001312 | 0.243 |
| 10 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2d5f2b2c02d77766434d9e5033b4a76c | 2cf49829391aa7891e877f2ed070adf0 | 2.758314 | 0.045003 | NaN | ... | brute | -1 | 100 | 0.882 | 17.730265 | 0.042344 | 0.663 | 0.155571 | 0.155571 | 0.219 |
| 13 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | efac583623711d395ddae7a1e881ff68 | 2cf49829391aa7891e877f2ed070adf0 | 2.131869 | 0.024922 | NaN | ... | brute | 1 | 5 | 0.757 | 0.265394 | 0.011031 | 1.000 | 8.032832 | 8.039768 | 0.243 |
| 14 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | efac583623711d395ddae7a1e881ff68 | 2cf49829391aa7891e877f2ed070adf0 | 0.022717 | 0.000942 | NaN | ... | brute | 1 | 5 | 1.000 | 4.083309 | 0.043806 | 0.922 | 0.005563 | 0.005564 | 0.078 |
| 16 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | b79d63bb7670c492de5c3befac58fe29 | 2cf49829391aa7891e877f2ed070adf0 | 1.345079 | 0.016867 | NaN | ... | brute | 1 | 1 | 0.663 | 4.171077 | 0.048267 | 0.929 | 0.322478 | 0.322499 | 0.266 |
| 19 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | e70d8e7886766d41f30889506baa1e67 | 88843f54689e3271092f70126e1de585 | 1.637761 | 0.036030 | NaN | ... | brute | -1 | 1 | 0.896 | 0.265624 | 0.007487 | 1.000 | 6.165711 | 6.168160 | 0.104 |
| 20 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | e70d8e7886766d41f30889506baa1e67 | 88843f54689e3271092f70126e1de585 | 0.005410 | 0.003306 | NaN | ... | brute | -1 | 1 | 1.000 | 4.144956 | 0.061061 | 0.922 | 0.001305 | 0.001305 | 0.078 |
| 22 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 22d5eac4a4146149b35eae6914921514 | 88843f54689e3271092f70126e1de585 | 2.464218 | 0.055673 | NaN | ... | brute | -1 | 5 | 0.922 | 4.122409 | 0.070032 | 0.896 | 0.597762 | 0.597848 | 0.026 |
12 rows × 22 columns
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | n_jobs | n_neighbors | mean_duration_onnx | std_duration_onnx | accuracy_score_onnx | speedup | std_speedup | sklearn_profiling | onnx_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.012 | 0.001 | 6.665 | 0.0 | -1 | 1 | 18.017 | 0.143 | 0.663 | 0.001 | 0.001 | See | See |
| 3 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.012 | 0.000 | 6.621 | 0.0 | -1 | 5 | 0.324 | 0.008 | 1.000 | 0.037 | 0.037 | See | See |
| 6 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.012 | 0.001 | 6.541 | 0.0 | 1 | 100 | 17.684 | 0.045 | 0.882 | 0.001 | 0.001 | See | See |
| 9 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.013 | 0.001 | 6.265 | 0.0 | -1 | 100 | 0.333 | 0.010 | 1.000 | 0.038 | 0.038 | See | See |
| 12 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.012 | 0.000 | 6.777 | 0.0 | 1 | 5 | 4.088 | 0.050 | 0.896 | 0.003 | 0.003 | See | See |
| 15 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.013 | 0.001 | 6.194 | 0.0 | 1 | 1 | 0.266 | 0.009 | 1.000 | 0.049 | 0.049 | See | See |
| 18 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.005 | 0.000 | 0.350 | 0.0 | -1 | 1 | 4.162 | 0.071 | 0.929 | 0.001 | 0.001 | See | See |
| 21 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.005 | 0.000 | 0.348 | 0.0 | -1 | 5 | 0.272 | 0.008 | 1.000 | 0.017 | 0.017 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | n_jobs | n_neighbors | mean_duration_onnx | std_duration_onnx | accuracy_score_onnx | speedup | std_speedup | sklearn_profiling | onnx_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.028 | 0.261 | 0.000 | 0.002 | -1 | 1 | 0.334 | 0.013 | 1.000 | 6.073 | 6.078 | See | See |
| 2 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.026 | 0.002 | 0.000 | 0.026 | -1 | 1 | 17.823 | 0.266 | 0.757 | 0.001 | 0.001 | See | See |
| 4 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.777 | 0.044 | 0.000 | 0.003 | -1 | 5 | 17.679 | 0.066 | 0.882 | 0.157 | 0.157 | See | See |
| 5 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.025 | 0.002 | 0.000 | 0.025 | -1 | 5 | 0.339 | 0.008 | 1.000 | 0.072 | 0.072 | See | See |
| 7 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.158 | 0.025 | 0.000 | 0.002 | 1 | 100 | 0.334 | 0.007 | 1.000 | 6.462 | 6.463 | See | See |
| 8 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.023 | 0.001 | 0.000 | 0.023 | 1 | 100 | 17.727 | 0.051 | 0.757 | 0.001 | 0.001 | See | See |
| 10 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.758 | 0.045 | 0.000 | 0.003 | -1 | 100 | 17.730 | 0.042 | 0.663 | 0.156 | 0.156 | See | See |
| 11 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.024 | 0.002 | 0.000 | 0.024 | -1 | 100 | 0.337 | 0.009 | 1.000 | 0.073 | 0.073 | See | See |
| 13 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.132 | 0.025 | 0.000 | 0.002 | 1 | 5 | 0.265 | 0.011 | 1.000 | 8.033 | 8.040 | See | See |
| 14 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.023 | 0.001 | 0.000 | 0.023 | 1 | 5 | 4.083 | 0.044 | 0.922 | 0.006 | 0.006 | See | See |
| 16 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 1.345 | 0.017 | 0.001 | 0.001 | 1 | 1 | 4.171 | 0.048 | 0.929 | 0.322 | 0.322 | See | See |
| 17 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.021 | 0.001 | 0.000 | 0.021 | 1 | 1 | 0.260 | 0.005 | 1.000 | 0.079 | 0.079 | See | See |
| 19 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 1.638 | 0.036 | 0.000 | 0.002 | -1 | 1 | 0.266 | 0.007 | 1.000 | 6.166 | 6.168 | See | See |
| 20 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.005 | 0.003 | 0.000 | 0.005 | -1 | 1 | 4.145 | 0.061 | 0.922 | 0.001 | 0.001 | See | See |
| 22 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 2.464 | 0.056 | 0.000 | 0.002 | -1 | 5 | 4.122 | 0.070 | 0.896 | 0.598 | 0.598 | See | See |
| 23 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.007 | 0.002 | 0.000 | 0.007 | -1 | 5 | 0.262 | 0.006 | 1.000 | 0.026 | 0.026 | See | See |
KNeighborsClassifier_kd_tree¶onnx (1.10.1) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=kd_tree.
| estimator | function | n_samples_train | n_samples | n_features | parameters_digest | dataset_digest | mean_duration_sklearn | std_duration_sklearn | n_iter | ... | algorithm | n_jobs | n_neighbors | accuracy_score_sklearn | mean_duration_onnx | std_duration_onnx | accuracy_score_onnx | speedup | std_speedup | diff_accuracy_scores | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | fe8267e25dadb302ed498e50fabf7ef4 | 1eb6cf1a720a225efb91df0b529b0510 | 0.882532 | 1.124641 | NaN | ... | kd_tree | -1 | 1 | 0.929 | 2.949033 | 0.275870 | 1.000 | 0.299261 | 0.300568 | 0.071 |
| 2 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | fe8267e25dadb302ed498e50fabf7ef4 | 1eb6cf1a720a225efb91df0b529b0510 | 0.003396 | 0.000762 | NaN | ... | kd_tree | -1 | 1 | 1.000 | 138.313347 | 0.000000 | 0.946 | 0.000025 | 0.000025 | 0.054 |
| 4 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | dc74b969bf622bc24ba3bc62c980983b | 1eb6cf1a720a225efb91df0b529b0510 | 1.098293 | 0.383205 | NaN | ... | kd_tree | -1 | 5 | 0.946 | 140.391716 | 0.000000 | 0.951 | 0.007823 | 0.007823 | 0.005 |
| 7 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 41accfcdcd5c50784bedf6164b63de99 | 1eb6cf1a720a225efb91df0b529b0510 | 5.737746 | 0.794953 | NaN | ... | kd_tree | 1 | 100 | 0.951 | 2.944724 | 0.187431 | 1.000 | 1.948483 | 1.952426 | 0.049 |
| 8 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 41accfcdcd5c50784bedf6164b63de99 | 1eb6cf1a720a225efb91df0b529b0510 | 0.003289 | 0.000942 | NaN | ... | kd_tree | 1 | 100 | 1.000 | 141.171351 | 0.000000 | 0.946 | 0.000023 | 0.000023 | 0.054 |
| 10 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 022f7445d43bb1dbc24dc3106c03cb93 | 1eb6cf1a720a225efb91df0b529b0510 | 3.216986 | 0.250691 | NaN | ... | kd_tree | -1 | 100 | 0.951 | 139.253027 | 0.000000 | 0.929 | 0.023102 | 0.023102 | 0.022 |
| 13 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 84622ba45e941db642965553529e1941 | 1eb6cf1a720a225efb91df0b529b0510 | 1.659354 | 0.213759 | NaN | ... | kd_tree | 1 | 5 | 0.946 | 0.006020 | 0.000230 | 1.000 | 275.634362 | 275.835459 | 0.054 |
| 14 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 84622ba45e941db642965553529e1941 | 1eb6cf1a720a225efb91df0b529b0510 | 0.001505 | 0.000416 | NaN | ... | kd_tree | 1 | 5 | 1.000 | 0.047670 | 0.006143 | 0.911 | 0.031572 | 0.031833 | 0.089 |
| 16 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | a9455565db1d8e052a783317c99744ff | 1eb6cf1a720a225efb91df0b529b0510 | 0.936813 | 0.277644 | NaN | ... | kd_tree | 1 | 1 | 0.929 | 0.066047 | 0.002241 | 0.894 | 14.184025 | 14.192185 | 0.035 |
| 19 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | fe8267e25dadb302ed498e50fabf7ef4 | edf7cb014c2c0910e1c3aaaf8ae633f2 | 0.035003 | 0.014955 | NaN | ... | kd_tree | -1 | 1 | 0.891 | 0.005915 | 0.000503 | 1.000 | 5.918086 | 5.939464 | 0.109 |
| 20 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | fe8267e25dadb302ed498e50fabf7ef4 | edf7cb014c2c0910e1c3aaaf8ae633f2 | 0.002949 | 0.000312 | NaN | ... | kd_tree | -1 | 1 | 1.000 | 0.043179 | 0.002485 | 0.911 | 0.068293 | 0.068406 | 0.089 |
| 22 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | dc74b969bf622bc24ba3bc62c980983b | edf7cb014c2c0910e1c3aaaf8ae633f2 | 0.031504 | 0.004727 | NaN | ... | kd_tree | -1 | 5 | 0.911 | 0.043827 | 0.002733 | 0.891 | 0.718830 | 0.720227 | 0.020 |
12 rows × 22 columns
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | n_jobs | n_neighbors | mean_duration_onnx | std_duration_onnx | accuracy_score_onnx | speedup | std_speedup | sklearn_profiling | onnx_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 2.844 | 0.046 | 0.028 | 0.0 | -1 | 1 | 140.461 | 0.000 | 0.929 | 0.020 | 0.020 | See | See |
| 3 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 4.413 | 0.068 | 0.018 | 0.0 | -1 | 5 | 2.966 | 0.331 | 1.000 | 1.488 | 1.497 | See | See |
| 6 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 4.395 | 0.042 | 0.018 | 0.0 | 1 | 100 | 140.524 | 0.000 | 0.951 | 0.031 | 0.031 | See | See |
| 9 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 4.387 | 0.056 | 0.018 | 0.0 | -1 | 100 | 2.982 | 0.267 | 1.000 | 1.471 | 1.477 | See | See |
| 12 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 4.472 | 0.085 | 0.018 | 0.0 | 1 | 5 | 0.047 | 0.016 | 0.891 | 95.243 | 100.830 | See | See |
| 15 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 4.419 | 0.056 | 0.018 | 0.0 | 1 | 1 | 0.006 | 0.000 | 1.000 | 728.000 | 728.843 | See | See |
| 18 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.001 | 0.021 | 0.0 | -1 | 1 | 0.066 | 0.003 | 0.894 | 0.012 | 0.012 | See | See |
| 21 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.001 | 0.015 | 0.0 | -1 | 5 | 0.006 | 0.001 | 1.000 | 0.182 | 0.183 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | n_jobs | n_neighbors | mean_duration_onnx | std_duration_onnx | accuracy_score_onnx | speedup | std_speedup | sklearn_profiling | onnx_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 0.883 | 1.125 | 0.000 | 0.001 | -1 | 1 | 2.949 | 0.276 | 1.000 | 0.299 | 0.301 | See | See |
| 2 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.003 | 0.001 | 0.000 | 0.003 | -1 | 1 | 138.313 | 0.000 | 0.946 | 0.000 | 0.000 | See | See |
| 4 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 1.098 | 0.383 | 0.000 | 0.001 | -1 | 5 | 140.392 | 0.000 | 0.951 | 0.008 | 0.008 | See | See |
| 5 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.004 | 0.002 | 0.000 | 0.004 | -1 | 5 | 2.980 | 0.326 | 1.000 | 0.001 | 0.001 | See | See |
| 7 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 5.738 | 0.795 | 0.000 | 0.006 | 1 | 100 | 2.945 | 0.187 | 1.000 | 1.948 | 1.952 | See | See |
| 8 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.003 | 0.001 | 0.000 | 0.003 | 1 | 100 | 141.171 | 0.000 | 0.946 | 0.000 | 0.000 | See | See |
| 10 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 3.217 | 0.251 | 0.000 | 0.003 | -1 | 100 | 139.253 | 0.000 | 0.929 | 0.023 | 0.023 | See | See |
| 11 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.006 | 0.001 | 0.000 | 0.006 | -1 | 100 | 3.009 | 0.318 | 1.000 | 0.002 | 0.002 | See | See |
| 13 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 1.659 | 0.214 | 0.000 | 0.002 | 1 | 5 | 0.006 | 0.000 | 1.000 | 275.634 | 275.835 | See | See |
| 14 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.002 | 0.000 | 0.000 | 0.002 | 1 | 5 | 0.048 | 0.006 | 0.911 | 0.032 | 0.032 | See | See |
| 16 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 0.937 | 0.278 | 0.000 | 0.001 | 1 | 1 | 0.066 | 0.002 | 0.894 | 14.184 | 14.192 | See | See |
| 17 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 1 | 0.005 | 0.000 | 1.000 | 0.203 | 0.204 | See | See |
| 19 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.035 | 0.015 | 0.000 | 0.000 | -1 | 1 | 0.006 | 0.001 | 1.000 | 5.918 | 5.939 | See | See |
| 20 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.003 | 0.000 | 0.000 | 0.003 | -1 | 1 | 0.043 | 0.002 | 0.911 | 0.068 | 0.068 | See | See |
| 22 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.032 | 0.005 | 0.001 | 0.000 | -1 | 5 | 0.044 | 0.003 | 0.891 | 0.719 | 0.720 | See | See |
| 23 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.002 | 0.000 | 0.000 | 0.002 | -1 | 5 | 0.006 | 0.001 | 1.000 | 0.405 | 0.417 | See | See |
HistGradientBoostingClassifier_best¶onnx (1.10.1) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: learning_rate=0.01, n_iter_no_change=10.0, max_leaf_nodes=100.0, max_bins=255.0, min_samples_leaf=100.0, max_iter=300.0.
| estimator | function | n_samples_train | n_samples | n_features | parameters_digest | dataset_digest | mean_duration_sklearn | std_duration_sklearn | n_iter | ... | max_leaf_nodes | min_samples_leaf | n_iter_no_change | accuracy_score_sklearn | mean_duration_onnx | std_duration_onnx | accuracy_score_onnx | speedup | std_speedup | diff_accuracy_scores | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | HistGradientBoostingClassifier_best | predict | 100000 | 1000 | 100 | 25b9f14bed7dd5d830c6ccd4dfebbf0c | 8c8fffa8ec4b2d8de833421f9e32beab | 0.165556 | 0.008624 | 300 | ... | 100 | 100 | 10 | 0.824 | 0.444116 | 0.01947 | 1.0 | 0.372776 | 0.373134 | 0.176 |
1 rows × 25 columns
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | mean_duration_onnx | std_duration_onnx | accuracy_score_onnx | speedup | std_speedup | sklearn_profiling | onnx_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | HistGradientBoostingClassifier_best | fit | 100000 | 100000 | 100 | 125.267 | 0.0 | 300 | 0.001 | 0.001 | 0.534 | 0.026 | 0.824 | 234.499 | 234.786 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | mean_duration_onnx | std_duration_onnx | accuracy_score_onnx | speedup | std_speedup | sklearn_profiling | onnx_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | HistGradientBoostingClassifier_best | predict | 100000 | 1000 | 100 | 0.166 | 0.009 | 300 | 0.005 | 0.0 | 0.444 | 0.019 | 1.0 | 0.373 | 0.373 | See | See |